CN111862707A

CN111862707A - Method and equipment for evaluating user memory level in language translation learning

Info

Publication number: CN111862707A
Application number: CN202010568052.4A
Authority: CN
Inventors: 周海滨
Original assignee: Beijing Guoyin Redwood Education Technology Co ltd
Current assignee: Beijing Guoyin Redwood Education Technology Co ltd
Priority date: 2020-06-19
Filing date: 2020-06-19
Publication date: 2020-10-30

Abstract

The invention relates to the technical field of intelligent memory methods, in particular to a method and equipment for evaluating memory level of a user in language translation learning, wherein the method comprises the steps of obtaining learning information of the user, wherein the learning information comprises the correct rate of answering a learning word by the user; generating a gear for evaluating the memory level of the user according to the correct rate of the user to answer the learning words; the generation of the gears effectively reflects the memory level of the user, solves the technical problem that an individualized learning plan cannot be formulated according to different memory levels of different users, generates the technical effects of improving the learning efficiency and more effectively utilizing the learning time, and can also improve the learning interest of the user so as to generate the power for the user to learn.

Description

Method and equipment for evaluating user memory level in language translation learning

The technical field is as follows:

the invention relates to the technical field of intelligent memory methods, in particular to a method and equipment for evaluating memory level of a user in language translation learning.

Background art:

with the globalization of popularization, language is the basis for people to communicate with. Since China added WTO, it raised a lot of foreign language learning heat. In the learning engineering of foreign languages, the memory of foreign language words is the most basic, so learners often need to memorize a large number of words to tamp the basis of learning english. Real-world teachers often make a uniform word learning plan for the students of a class, but the learning plan is often not specifically adapted to each learner due to the different memory level of each learner.

The invention is provided in view of the above.

The invention content is as follows:

the invention provides a method and equipment for evaluating memory level of a user in language inter-translation learning, which can evaluate the memory level of different users when the user learns words.

The invention provides a method for evaluating user memory level in language translation learning, which comprises the following steps: acquiring learning information of a user, wherein the learning information comprises the correct rate of answering a learning word by the user; and generating a gear for evaluating the memory level of the user according to the correct rate of the user to answer the learning words.

By adopting the scheme, the accuracy rate of the user answering the learning words can comprise the accuracy rate of the user answering in the historical information and the accuracy rate of the current user answering; the gear for measuring the memory level of the user is determined according to the total correct rate of the user for answering the learning words, wherein the higher the correct rate is, the faster the user memorizes the learning words and the better the memory level is, the higher the gear is, otherwise, the lower the gear is.

Further, the learning information includes beginner information and review information, the correct rate of the user's response to the learning word includes a first correct rate, the first correct rate is calculated by Rrr Crr/Crt, where Rrr is the first correct rate of the user's response to the learning word, Crr is the number of times the user answers the learning word during review, and Crt is the total number of times the user answers the learning word during review.

Further, the learning information further includes test information, the correctness rate of the user answering the learning word includes a second correctness rate, and the calculation formula of the second correctness rate is: rrt ═ i (Crr + Cqr)/(Crt + Cqt), where Rrt is the second rate of correctness, Cqr is the number of times the user answered the learned word in the test, and Cqt is the total number of times the user answered the learned word in the test.

By adopting the scheme, the testing stage can be set for learning the learning words, the testing stage can exist independently of the reviewing stage, all words can be tested uniformly after the user finishes learning the words of a certain chapter, the system can also be used for performing spot test in a regular or irregular mode, the setting of the testing stage can break the conventional reviewing so as to enhance the learning effect of the user, the evaluation of the accuracy rate can be more objective and authoritative by adding the times in the testing information in the process of counting the accuracy rate, and the second accuracy rate is the user answering accuracy rate calculated by integrating the answering times in the reviewing stage and the testing stage.

Further, the number of times the user answered the learning word in the test is calculated as: calculating the optimal review time point after the user finishes learning the words each time according to the learning information to obtain the (N-1) th optimal review time point after the (N-1) th learning is finished, wherein N is the number of times that the user finishes learning the words at the current time, determining the current test time point according to the test information, and calculating a first time interval Tit-Tq-Tbr 1, wherein Tq is the current test time point, and Tbr1 is the (N-1) th optimal review time point; when Tit < Tx, the increase in Cqr is 0; when Tit > Ts, the incremental value of Cqr is 2; when Tx ≦ Tit ≦ Ts, the incremental value of Cqr is (1+ Tit/Ts); tx is the lower limit interval duration and Ts is the upper limit interval duration.

By adopting the scheme, the current testing time point is compared with the optimal time point generated after the last learning is finished, namely the (N-1) th optimal review time point is compared, because the (N-1) th optimal review time point is the time point for re-learning in normal review, if the current testing time point is different from the current testing time point, the correct times cannot be determined by one-time calculation according to the answer-to-answer according to the rule of forgetting the curve by human; and if the difference value between the current testing time point and the (N-1) th best review time point is different, the obtained correct times of the user for answering the word are different.

Specifically, the total number of times that the user answers the learned word in the test is calculated as: cqt ═ Cqr + Cqw, the Cqw is the total number of times the user wrote the learned word, the calculation of Cqw is: when Tit < Tx, the increase in Cqw is 2; when Tit > Ts, the incremental value of Cqw is 0; when Tx ≦ Tit ≦ Ts, the incremental value of Cqw is (1-Tit/Ts).

By adopting the scheme, the number of wrong answers influences the total number of answers, and further influences the answer accuracy.

Specifically, the gear in which the learning word is located is calculated as: receiving the second accuracy; judging the range of the second accuracy; and determining the gear according to the range of the second accuracy.

By adopting the scheme, the gears reflect the memory speed of the user, so the different second accuracy rates reflect the memory level of the user for different words, different gears are set according to the ranges of the different second accuracy rates, and the gears are divided more scientifically and reasonably because the memory speed of human is not increased in proportion to the answering accuracy rate.

Further, calculating the (N-1) th optimal review time point includes:

when the (N-1) th learning information is the beginner information, determining whether the learning words are new words or mature words according to the beginner information;

when the learning word is a doneness word, the (N-1) th best review time point is not calculated;

when the learning word is a new word, Tbr1 is Ti + Di, and Di is C1 × e^pAnd P is (C2 multiplied by Si/mu) + C3, wherein T1 is an initial learning time point, Di is an initial learning review interval duration, C1 is a power coefficient, e is a natural constant, P is a power value, C2 is an intensity coefficient, Si is initial memory intensity, C3 is a power constant, and mu is a calculation constant.

By adopting the scheme, the values of C1, e, C2, C3 and mu are determined according to a human forgetting curve, the memory strength represents the grasping degree of a user on words or sentences, the grasping degree can be represented by numerical values, and the higher the memory strength value is, the higher the grasping degree of the user on the words is.

Further, the determination of the initial memory strength value may be setting an upper limit reaction duration and a lower limit reaction duration, when the initial learning information is that the user answers the learning word and the answering duration is less than or equal to the lower limit reaction duration, the learning word is marked as a cooked word and the memory strength value is the first initial memory strength value; the first learning information is that the user answers the learning word, the answering time is longer than the lower limit reaction time and is less than or equal to the upper limit reaction time, the learning word is marked as a new word, the memory intensity value is a third initial memory intensity value, the calculation formula is I ═ Dz- (D3-Db) x 2, Dz is an extreme value, I is the third initial memory intensity value, D3 is the actual reaction time, Da is the upper limit reaction time, and Db is the lower limit reaction time; the first time learning information is wrong for the user when the learning word or the answering time exceeds the upper limit reaction time, the learning word is marked as a new word, and the memory strength value is the second initial memory strength value.

By adopting the scheme, another implementation mode of marking words and copying initial memory strength according to different initial learning information is provided, the word memory strength calculation method by the English-Chinese interconversion learning mode further comprises the steps of setting an upper limit reaction time length and a lower limit reaction time length, so that the memory strength value of the learning words for the user can be identified more accurately and more finely, the upper limit reaction time length and the lower limit reaction time length can be determined according to actual conditions, and the user answers in the time length less than or equal to the lower limit reaction time length, which indicates that the user has high mastering degree on the learning words; when the user answering time exceeds the upper limit reaction time, the user is considered to be overtime answering, which indicates that the user has low word mastery and needs to think for a long time to answer, so that the overtime answering setting avoids the excessive time consumption of the user, and the user is considered not to master the learning word no matter how long the answering time is under the same condition of wrong answering; when the user answers between the upper limit reaction duration and the lower limit reaction duration, the user still answers, and the learning word is proved to have a certain mastery degree but not to be high, at this time, the memory intensity value given to the user for the learning word is a third initial memory intensity value, the third initial memory intensity value is larger than the second initial memory intensity value but smaller than the first initial memory intensity value, the size of the initial memory intensity value can be determined according to the actual situation, the third initial memory intensity value can be calculated according to a formula I (Da- (D3-Db) multiplied by 2) because of the difference of the answering durations, I is the third initial memory intensity value, D3 is the actual reaction duration, Da is the upper limit reaction duration, and Db is the lower limit reaction duration.

Preferably, when the (N-1) -th learning information is the review information, Tbr1 ═ Tr + Dr, Dr ═ C1 × e^pAnd P is (C2 multiplied by Sr/mu) + C3, wherein Tr is the time point when the (N-1) th learning is completed, Dr is the duration of the review interval, and Sr is the memory strength of the learned word after the (N-1) th learning is completed.

By adopting the scheme, different from the initial learning, the number of times of reviewing can be multiple, so that the memory intensity value after each learning is completed is overlapped or subtracted, the memory intensity of the learning word after the (N-1) th learning is completed is different after each reviewing, and the (N-1) th optimal reviewing time point can be calculated according to the specific condition of each learning completion.

Preferably, the number of times of continuous answer pairs of the learning words is judged; if the number of times is equal to three times, judging whether the optimal review time point generated after the third answer is finished and the continuous three-time answer pair time are in the same review period; if yes, setting the optimal review time point generated after the third answer in the next review period.

By adopting the scheme, the optimal review time point is adjusted reasonably by combining the human forgetting curve and the human physiological characteristics.

Further, when the (N-1) th learning information is the test information, the determination of the (N-1) th best time point needs to be according to the word generation or the word maturity when the word is tested and the (N-1) th learning is the test, and the memory intensity value determined after the learning is finished is recorded as Sq. When the user answers the cooked words in the testing stage, the memory intensity of the cooked words is not changed; when the user wrongly answers the cooked word in the testing stage, the cooked word is marked as an original word again, and the memory strength value is changed into a second initial memory strength value; when the user wrongly answers the new word, the memory intensity value of the new word is reduced; when the user answers the new word, the memory strength value of the new word is increased.

By adopting the scheme, the test information comprises the answering condition of the same user in the test stage, the ripe words can appear in the test, and when the user answers wrong ripe words, the user is considered that the mastery degree of the ripe words is low due to the influence of forgetting factors, and the learned words need to be learned again, so that the memory intensity value marked as the new words is changed into the second initial memory intensity value; when the user wrongly answers the new word, the memory intensity value of the new word is reduced, and the reduced value is directly reduced for the new word test; when the user answers the new word, the memory strength value of the new word is increased, and the added value is directly added to the new word test. The test can be carried out on the user at regular time through manual arrangement, or can be automatically arranged for the user after each chapter of the word bank is learned, and the influence of the test information on the memory intensity value and the influence of the review information on the memory intensity value are integrated, so that the mastering degree of the user on the learning words can be comprehensively and comprehensively reflected.

Further, the formula of the direct reduction value of the new word test is Sqr 16+16 × Rqw, Rqw Cqw/Cqt, where Sqr is the direct reduction value of the new word test, Rqw is the response error rate of the new word in the test, Cqw is the total number of times of the response error of the new word in the test, Cqt is the total number of times of the response error of the new word in the test, and a constant 16 in the formula is determined according to a human forgetting curve; by calculating the response error rate of the new words in the test and further calculating the memory strength value reduced by the new words in the test due to the response error according to the response error rate, the mastering degree of the user on the new words can be analyzed more accurately and more conveniently.

When Tit is less than 24 × 60 × 60, the calculation formula of the direct increase value of the new word test is Sqi ═ 14+12 × Meg × 0.2)/3; when Tit >3 × 24 × 60 × 60, the calculation formula of the new word test direct addition value is Sqi ═ (14+12 × Meg × 0.2); when 24 × 60 × 60 ≦ Tit ≦ 3 × 24 × 60 × 60, the calculation formula of the new word test direct added value is Sqi ═ (14+12 × Meg × 0.2)/2; sqi is a direct added value of the vocabulary test, Meg is a gear, and constants 14 and 12 in the formula are determined according to a human forgetting curve; by calculating the answer accuracy of the new words in the test and further calculating the memory strength value reduced by the answer to the new words in the test according to the answer accuracy, and by introducing the comparison between the test time point and the optimal review time point, the mastering degree of the user on the new words can be analyzed more accurately and more conveniently.

Further, Tbr1 is expressed as the (N-1) th best time point, so when the (N-1) th learning is the test and the test information is the word response, Tbr1 ═ Tq '+ Dq1, where Dq1 is the interval duration generated after the last learning is completed as the test and Tq' is the first test time point.

By adopting the scheme, the first test time point can be determined according to the test information and is the answering time when the last learning is the test. Reference formula Tbr1 Tr + Dr, Dr C1 × e^pP ═ C2 × Sr/10) + C3; the formula Tbr1 ═ Tq' + Dq1, Dq1 ═ C1 × e^pAnd P is (C2 × Sq/10) + C3, Sq is the memory strength value after the last learning is finished as the test, and the calculation of Sq is obtained by superposing the memory strength value in the history information and the calculation formula Sqi of the new word test direct increment value.

Further, when the (N-1) th learning is a test and the test information is a new word error and the test time point is later than the (N-1) th best review time point, Tbr1 ═ Tbr1 '+ Dq1, the Tbr 1' is the (N-2) th best review time point; when the test information is a new word error and the test time point is earlier than or equal to the first best review time point, Tbr1 ═ Tq' + Dq 1. In this case, the reference formula Tbr1 is Tr + Dr, and Dr is C1 × e^pP ═ C2 × Sr/10) + C3; the results show that Tbr1 ═ Tbr 1' + Dq1 and Dq1 ═ C1 × e ^pAnd P is (C2 × Sq/10) + C3, Sq is the memory strength value after the last learning is finished as the test, and the calculation of Sq is calculated by the memory strength value in the history information and the calculation formula of the direct reduction value of the new word test, Sqr.

Preferably, in the review process, the memory strength value increased or decreased in the review process is calculated on the original memory strength value each time the word generation is maximized, and the method comprises the following steps:

the added first fixed value indicates that the mastery degree of the new word by the user is increased, and the reduced second fixed value indicates that the mastery degree of the new word by the user is reduced; the first fixed value and the second fixed value can be adjusted according to the human forgetting curve and the initial memory intensity value.

Preferably, the first fixed value is smaller than the second fixed value.

By adopting the scheme, the time that the memory intensity of the new word reaches the full value can be prolonged when the first fixed value is smaller than the second fixed value, so that the review times of the new word by a user can be increased, and the impression of the user is further deepened.

Further, the method also comprises an added reaction duration influence value, and the calculation formula of the reaction duration influence value is as follows: and Rd is (1-Mrd/Da) multiplied by Srd, wherein Mrd is response time length, Srd is a reaction time length influence memory strength basic value, and Rd is a reaction time length influence value.

By adopting the scheme, the reaction duration influence memory intensity basic value Srd can be determined according to the overall assignment condition and the human forgetting curve, the reaction duration influence memory intensity basic value Srd is 8, the influence of the reaction duration on the memory intensity value is shown at most, and the answering duration unit of Mrd is second; by calculating the reaction duration influence value, the mastery degree of the user on the new words can be accurately and meticulously calculated according to the answering speed of the user.

Further, the memory strength increase value or decrease value further includes a fatigue influence value, and the calculation formula of the fatigue influence value is as follows: fa is (1-Fi) x Mfa, Fi is De/Ds, where Fa is a fatigue influence value, Fi is a fatigue index, Mfa is a fatigue index influence memory strength base value, De is a learning effective duration, and Ds is a fatigue set duration.

With the above scheme, the learning effective duration De is the time for the user to interact with the learning interface, and since the learning time of 30 minutes per day is most suitable according to the human forgetting curve, Ds can be set to 30 minutes, 30 × 60 is obtained by converting 30 minutes into 1800 seconds, the fatigue index influence memory strength basic value Mfa indicates how much the fatigue degree most influences the memory strength value, the longer the learning time is, the more tired the user is, the less the memory strength values are increased and decreased, and otherwise, the greater the memory strength values are increased and decreased. The fatigue influence value is fully considered from the physiological rule of the human body to influence the memory capacity, the increase and decrease of the memory intensity value are calculated more accurately and finely, and the fatigue influence value is obtained according to a human forgetting curve Mfa.

Further, the increased or decreased memory intensity value further includes a difficulty influence value, and the difficulty influence value is calculated by the following formula: df ═ Dti × Mdt, (Dm + Am), Dm ═ Rwr × λ, Rwr ═ Crw/Crt; df is a difficulty influence value, Dti is a difficulty index, Mdt is a difficulty index influence memory strength basic value, Dm is learning data calculation difficulty, Am is manual labeling difficulty, Rwr is the error rate of responding to the new words in the user review process, lambda is a difficulty mark, Crw is the sum of times of responding to the new words in the user review process and the initial learning process, and Crt is the total times of responding to the new words in the user review process.

By adopting the scheme, the difficulty influence value can comprise the manual marking difficulty and the learning data calculation difficulty; the learning data calculation difficulty is calculated through the error rate of the user answering the words; the difficulty mark lambda is used for calculating the learning data calculation difficulty and can be displayed on a response interface in the form of an energy grid, and the difficulty index influence memory intensity basic value Mdt is determined according to the overall assignment condition and a human forgetting curve and is expressed as the influence of word difficulty on the memory intensity value.

The test also has influence on the difficulty influence value to obtain a correction difficulty influence value, and the calculation of the correction difficulty influence value is as follows: df ═ Dti ' xmdt, Dti ═ Dm ' + Am, Dm ═ Rwr ' x λ, Rwr ═ Crw + Cqw/Crt + Cqt; df 'is a correction difficulty influence value, Dti' is a correction difficulty index, Mdt is a difficulty index influence memory strength basic value, Dm 'is a correction learning data calculation difficulty, Am is an artificial labeling difficulty, Rwr' is an error rate of answering the new word in the user review and test process, lambda is a difficulty mark, Crw is the sum of times of wrong answering the new word in the user review process and initial learning, Crt is the total times of answering the new word in the user review process, Cqw is the total times of wrong answering the new word in the test by the user, and Cqt is the total times of answering the new word in the test by the user.

By adopting the scheme, the degree of mastering the learning words by the user can be more accurately and meticulously analyzed by correcting the difficulty influence value through calculating and testing the change of the difficulty influence value.

Said increased or decreased memory intensity values further comprise an assiduous impact value, said assiduous impact value being calculated by the formula: dli Dgi × Mdg, Dgi ═ Trc-Tbr3)/24 × 60 × 60, where Dli is due diligence influence value, Dgi is due diligence influence index, Mdg is due diligence influence memory intensity base value, Tbr3 is the best review time point obtained after the current review is completed, and Trc is the current review time point.

By adopting the scheme, the memory intensity value is increased or decreased according to the review time of the user.

The increased memory strength value further includes a gear influence value, and the calculation formula of the gear influence increase value may be G1-Meg × 0.1 × Reg, where Meg is an engine gear and Reg is an engine answer constant.

By adopting the scheme, G1 is a gear influence added value, and the engine constant Reg is determined according to a human forgetting curve.

When the user reviews the new words, the reduced memory strength value further includes a gear influence reduction value, and a calculation formula of the gear influence reduction value may be G2 ═ Weg × Crw/Crt, where Weg is an engine constant for wrong answers, Crw is the total number of times of wrong answers to the learned new words in the review, and Crt is the total number of times of answers to the learned new words in the review.

With the adoption of the scheme, G2 is a gear influence reduction value, and the wrong-answer engine constant Weg is determined according to a human forgetting curve.

The invention also provides a device for applying the method for calculating the memory strength of the foreign language words in the language translation learning, which comprises the following steps: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the method for evaluating the memory level of the user in the language intertranslation learning.

The invention has the beneficial effects that:

1. the technical problem that the memory level of a user cannot be measured through word memory is well solved through setting of the gears, and then the technical effect that different users can make learning plans individually according to different gears of the users is achieved.

2, the technical problem of incomplete accuracy statistics is well solved by calculating the accuracy of answers in tests and review, and the effect of more accurate and comprehensive calculation of the accuracy is achieved.

3. By calculating the optimal review time point, the technical problem that the number of times of answering is unreasonable is solved, and the effect that the calculation accuracy is more accurate and comprehensive is achieved.

4. The difficulty influence value solves the problem of inaccurate memory strength caused by the fact that the difficulty of the word is not considered in calculation when a user learns; the reaction duration influence value solves the technical problem that the memory strength value cannot be determined due to the reaction speed during the learning of the user.

5. The diligence influence value solves the technical problem that the memory intensity value cannot be determined due to the morning and evening of the review time when a user learns; the test provides a more versatile and effective learning mode for the user.

Description of the drawings:

in order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

FIG. 1 is a schematic flow chart of one embodiment of the present invention;

FIG. 2 is a flowchart illustrating one embodiment of calculating the correct rate of learning words answered by a user in a test;

FIG. 3 is a schematic diagram of a user answering according to an embodiment of the present invention;

FIG. 4 is a diagram illustrating a user response result according to an embodiment of the present invention;

fig. 5 is a schematic diagram of a human forgetting curve.

The specific implementation mode is as follows:

reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

The words in the text can refer to but are not limited to English words, and in order to facilitate unified calculation, the operation units related to duration are unified into seconds; the time points may be in a time stamp manner, i.e., the number of seconds elapsed from 1/00: 00/1970 to the corresponding time point.

Referring to fig. 1, fig. 3 and fig. 4, a method for evaluating a memory level of a user in language translation learning includes the following steps: acquiring learning information of a user, wherein the learning information comprises the correct rate of answering a learning word by the user; and generating a gear for evaluating the memory level of the user according to the correct rate of the user to answer the learning words.

By adopting the scheme, the method for evaluating the memory level of the user in the language translation learning can be realized through computer software or a mobile phone APP (application), and the like of the user, the user can firstly select any word bank, such as a college English four-level or six-level word bank or a business English word bank, and then can select the intelligent memory module for learning, wherein the intelligent memory module is used for enabling the user to answer Chinese by reading English or answer English by reading Chinese; corresponding words in the selected word stock can appear on the display interface, and the intelligent memory module is used for enabling a user to know the Chinese meaning or not by reading English or whether the user can know the English meaning or not by reading Chinese; corresponding words in the selected lexicon appear on the display interface, the user can select the smiling face or the crying face in fig. 3 to answer, the smiling face indicates that the learning words are known and the crying face indicates that the learning words are not known, then the interface in fig. 4 appears, and the user can select to check or cross to determine whether to answer the words or to answer the words in a wrong way; the gears are named only one, and similar names of levels, grades and the like are all covered in the protection scope of the invention.

The learning information comprises beginner information and review information, the correct rate of the user to answer the learning words comprises a first correct rate, the first correct rate is calculated as Rrr being Crr/Crt, wherein Rrr is the first correct rate of the user to answer the learning words, Crr is the number of times the user answers the learning words in the review process, and Crt is the total number of times the user answers the learning words in the review process.

By adopting the scheme, the relearning information is relative to the beginner information, the beginner information is information that the user answers the learning words for the first time, the words appearing for the first time may have the situation that the user knows the learning words, if the learning words are counted again in the gear calculation, the influence on measuring the memory level of the user is inaccurate, and therefore the frequency of learning the learning words for the first time is not involved in the gear calculation; the review information comprises the review after the first beginner of the user is finished, and the human brain can forget, so the study needs to be reviewed; the accuracy is calculated by distinguishing a beginner stage and a review stage and calculating the number of answer pairs, so that the gears are calculated more reasonably and comprehensively by visitors; the words appearing in the review information can be the words which are wrongly answered in the initial learning of the user, the words which are answered in the initial learning are not included, and the answering times can be calculated more accurately and objectively.

The learning information further comprises test information, the accuracy of the user answering the learning word comprises a second accuracy, and a calculation formula of the second accuracy is as follows: rrt ═ i (Crr + Cqr)/(Crt + Cqt), where Rrt is the second rate of correctness, Cqr is the number of times the user answered the learned word in the test, and Cqt is the total number of times the user answered the learned word in the test.

By adopting the scheme, the testing stage can be set for learning the learning words, the testing stage can exist independently of the reviewing stage, all words can be tested uniformly after the user finishes learning the words of a certain chapter, the system can also be used for performing spot test in a regular or irregular mode, the conventional reviewing can be broken through by the setting of the testing stage, the learning effect of the user is enhanced, and the accuracy can be evaluated more objectively and authoritatively by adding the times of the testing information in the process of counting the accuracy.

Referring to fig. 2 and 5, the number of times the user answers the learning word in the test is calculated as: calculating the optimal review time point after the user finishes learning the words each time according to the learning information to obtain the (N-1) th optimal review time point after the (N-1) th learning is finished, wherein N is the number of times that the user finishes learning the words at the current time, determining the current test time point according to the test information, and calculating a first time interval Tit-Tq-Tbr 1, wherein Tq is the current test time point, and Tbr1 is the (N-1) th optimal review time point; when Tit < Tx, the increase in Cqr is 0; when Tit > Ts, the incremental value of Cqr is 2; when Tx ≦ Tit ≦ Ts, the incremental value of Cqr is (1+ Tit/Ts); tx is the lower limit interval duration and Ts is the upper limit interval duration.

By adopting the scheme, the optimal review time point is the time point with the best memory enhancing effect when the human needs to remember the learning words, the test is possibly carried out randomly, so the current test time point is compared with the optimal time point generated after the last learning is finished, namely the (N-1) th optimal review time point is compared, because the (N-1) th optimal review time point is the time point for learning again in the normal review, if the current test time point is different from the current test time point, the correct times cannot be determined according to the answer-to-once calculation according to the rule of a human forgetting curve, when the Tit < Tx, the user is considered to be in the answer-to-answer time, so the answer-to-answer times are not increased, when the Tit > Ts, the user is considered to have been forgotten, so the answer-to-times are increased by 2; and obtaining the inflection point of the frequency calculation in seven days before and after the optimal review time point according to the human forgetting curve, wherein Tx is-7 multiplied by 24 multiplied by 60, T is 7 multiplied by 24 multiplied by 60, and 7 multiplied by 24 multiplied by 60 is the expression of converting seven days into seconds, and the difference between the current testing time point and the (N-1) th optimal review time point is different, so that the correct times of answering the word by the obtained user are different. The method starts from the physiological rule of human reasonably, so that the calculation of the accuracy is more scientific.

The total number of times that the user answers the learned word in the test is calculated as: cqt ═ Cqr + Cqw, the Cqw is the total number of times the user wrote the learned word, the calculation of Cqw is: when Tit < Tx, the increase in Cqw is 2; when Tit > Ts, the incremental value of Cqw is 0; when Tx ≦ Tit ≦ Ts, the incremental value of Cqw is (1-Tit/Ts).

By adopting the scheme, the times of wrong answers in the test cannot be summarized according to the rule of the human forgetting curve, and when Tit is less than Tx, the user is considered to be in the time of answering pairs, so that the times of wrong answers are increased by 2; when Tit is greater than Ts, the user is considered to be in a forgetting period, so that the number of wrong answers is not increased; when Tx is less than or equal to Tit is less than or equal to Ts, the calculation can be reasonably carried out according to the formula.

The gear of the learning word is calculated as: receiving the second accuracy; judging the range of the second accuracy; and determining the gear according to the range of the second accuracy.

By adopting the scheme, the gear position value determining implementation mode is provided, the gear position for measuring the memory level of the user can be divided into 10 gear positions according to the difference of the second accuracy, and the difference between adjacent gear positions can be different, because the speed of human memory is not increased in proportion to the answer accuracy, the gear position division is realized more scientifically and reasonably; rrt is less than or equal to 5, and the gear value is 1; rrt is greater than 5 and less than or equal to 15, and the gear value is 2; rrt is greater than 15 and less than or equal to 25, and the gear value is 3; rrt is greater than 25 and less than or equal to 40, and the gear value is 4; rrt is greater than 40 and less than or equal to 60, and the gear value is 5; rrt is greater than 60 and less than or equal to 75, and the gear value is 6; rrt is greater than 75 and less than or equal to 85, and the gear value is 7; rrt is greater than 85 and less than or equal to 93, and the gear value is 8; rrt is greater than 93 and less than or equal to 98, and the gear value is 9; rrt is greater than 98 and the gear value is 10.

Calculating the (N-1) th optimal review time point includes:

By adopting the scheme, when the initial learning is marked as the mature word, the user is proved to have high mastery degree on the mature word, the mature word can be set without appearing in the subsequent review process in consideration of enabling the user to more pointedly memorize the word in a limited time, but the mature word can also be forgotten in consideration of not being memorized for a long time, and the test can be carried out on the mature word appearing in the test; the values of C1, e, C2, C3 and μ are determined according to a human forgetting curve, the value of C1 may be 1, e is 2.7183, the value of C2 may be 1.6, the value of C3 may be 0, and the value of μmay be 10; the memory strength represents the grasping degree of the user on the words or sentences, and can be represented by numerical values, and the higher the memory strength value is, the higher the grasping degree of the user on the words is.

The determination of the initial memory strength value can be setting an upper limit reaction duration and a lower limit reaction duration, when the initial learning information is that the user answers the learning word and the answering duration is less than or equal to the lower limit reaction duration, the learning word is marked as a cooked word and the memory strength value is a first initial memory strength value; the first learning information is that the user answers the learning word, the answering time is longer than the lower limit reaction time and is less than or equal to the upper limit reaction time, the learning word is marked as a new word, the memory intensity value is a third initial memory intensity value, the calculation formula is I ═ Dz- (D3-Db) x 2, Dz is an extreme value, I is the third initial memory intensity value, D3 is the actual reaction time, Da is the upper limit reaction time, and Db is the lower limit reaction time; the first time learning information is wrong for the user when the learning word or the answering time exceeds the upper limit reaction time, the learning word is marked as a new word, and the memory strength value is the second initial memory strength value.

By adopting the scheme, another implementation mode of marking words and copying initial memory strength according to different initial learning information is provided, the word memory strength calculation method by the English-Chinese interconversion learning mode further comprises setting an upper limit reaction time length and a lower limit reaction time length, the memory strength value of the learning words to the user can be identified more accurately and finely, the upper limit reaction time length and the lower limit reaction time length can be determined according to actual conditions, the extreme value can be set to be 40, for example, according to a human memory reaction rule, the upper limit reaction time length can be 20 seconds, the lower limit reaction time length can be 5 seconds, the user can answer within 5 seconds (including 5 seconds) correctly, and the learning degree of the user to the learning words is very high; when the answering time of the user exceeds 20 seconds, the user is considered to answer overtime, which indicates that the user has low word mastery and needs to think for a long time to answer, so that the overtime setting of the answer avoids the excessive time consumption of the user, and under the same condition of wrong answer, the user is considered not to master the learning words no matter how long the answering time is; when the user answers for more than 5 seconds and less than or equal to 20 seconds, the user still answers the word, and the learning degree of the user is proved to be certain, but not high, at this time, the memory intensity value given to the user for the learning word is the third initial memory intensity value, the third initial memory intensity value is more than the second initial memory intensity value and less than the first initial memory intensity value, the initial memory intensity value can be determined according to the actual situation, for example, the highest first initial memory intensity value is 100, the second initial memory intensity value is 10, the third initial memory intensity value can be calculated according to the formula I-Dz- (D3-Db) × 2 because of the difference of answering time length, I is the third initial memory intensity value, and 5 < D3 is less than or equal to 20. By adding the setting of the upper limit reaction time length and the lower limit reaction time length, the mastering degree of the learning words by the user can be further reflected more meticulously and accurately according to the time length of the user answering, and the concentration degree of the user can be increased, so that the user has a sense of urgency and the learning efficiency is increased.

When the (N-1) -th learning information is the review information, Tbr1 is Tr + Dr, and Dr is C1 × e^pAnd P is (C2 multiplied by Sr/mu) + C3, wherein Tr is the time point when the (N-1) th learning is completed, Dr is the duration of the review interval, and Sr is the memory strength of the learned word after the (N-1) th learning is completed.

Judging the times of continuous answering of the learning words; if the number of times is equal to three times, judging whether the optimal review time point generated after the third answer is finished and the continuous three-time answer pair time are in the same review period; if yes, setting the optimal review time point generated after the third answer in the next review period.

By adopting the scheme, the first optimal review time point is adjusted reasonably by combining the human forgetting rule and the human physiological characteristics, the review period can be one day, when the optimal review time point after three times of continuous answering of the learning words in the review process is still displayed on the same day, and the optimal review time point can be adjusted to six morning spots on the second day in consideration of the promotion effect of sleep on memory.

And when the (N-1) th learning information is test information, determining the (N-1) th best time point according to the fact that the word is a new word or a mature word when the word is tested and the (N-1) th learning is a test, and recording the memory intensity value determined after the learning is finished as Sq.

When the user answers the cooked words in the testing stage, the memory intensity of the cooked words is not changed; when the user wrongly answers the cooked word in the testing stage, the cooked word is marked as an original word again, and the memory strength value is changed into a second initial memory strength value; when the user wrongly answers the new word, the memory intensity value of the new word is reduced; when the user answers the new word, the memory strength value of the new word is increased.

The calculation formula of the new word test direct reduction value is Sqr 16+16 × Rqw, Rqw Cqw/Cqt, wherein Sqr is the new word test direct reduction value, Rqw is the response error rate of the new word in the test, Cqw is the total number of times of the new word in the test, Cqt is the total number of times of the new word in the test, and a constant 16 in the formula is determined according to a human forgetting curve; by calculating the response error rate of the new words in the test and further calculating the memory strength value reduced by the new words in the test due to the response error according to the response error rate, the mastering degree of the user on the new words can be analyzed more accurately and more conveniently.

Since Tbr1 is expressed as the (N-1) th best time point, when the (N-1) th learning is the test and the test information is the word reply, Tbr1 ═ Tq '+ Dq1, Dq1 is the interval time length generated after the last learning is completed as the test, and Tq' is the first test time point.

When the (N-1) th learning is a test and the test information is a new word wrong answer and the test time point is later than the (N-1) th best review time point, Tbr1 is Tbr1 '+ Dq1, the Tbr 1' is the (N-2) th best review time point; when the test information is a new word error and the test time point is earlier than or equal to the first best review time point, Tbr1 ═ Tq' + Dq 1. In this case, the reference formula Tbr1 is Tr + Dr, and Dr is C1 × e^pP ═ C2 × Sr/10) + C3; the results show that Tbr1 ═ Tbr 1' + Dq1 and Dq1 ═ C1 × e ^pP ═ C2 × Sq/10) + C3, Sq is completeThe memory strength value after the last learning is tested is calculated by a memory strength value in the historical information and a calculation formula Sqr of a direct reduction value of the new word test.

When in the review process, every time the user finishes answering to the new word, all can calculate the memory intensity value that the review process increases or reduces on original memory intensity value, calculates the memory intensity value that increases when answering the pair, calculates the memory intensity value that reduces when answering the wrong, includes:

The first fixed value is less than the second fixed value.

By adopting the scheme, the time that the memory intensity of the new word reaches the full value can be prolonged when the first fixed value is smaller than the second fixed value, so that the review times of the user on the new word can be increased, and the impression of the user can be further enhanced; for example, the first fixed value may be 2 and the second fixed value may be 9.

The method further comprises an added reaction duration influence value, and the calculation formula of the reaction duration influence value is as follows:

and Rd is (1-Mrd/Da) multiplied by Srd, wherein Mrd is response time length, Srd is a reaction time length influence memory strength basic value, and Rd is a reaction time length influence value.

The memory strength increasing value or the memory strength decreasing value further comprises a fatigue influence value, and the calculation formula of the fatigue influence value is as follows: fa is (1-Fi) x Mfa, Fi is De/Ds, where Fa is a fatigue influence value, Fi is a fatigue index, Mfa is a fatigue index influence memory strength base value, De is a learning effective duration, and Ds is a fatigue set duration.

By adopting the scheme, the learning effective duration De is the interaction time between the user and the learning interface, the learning time of 30 minutes per day can be obtained most suitably according to the human forgetting curve, and when the effective learning duration exceeds 30 minutes, the value of the effective learning duration is 30 minutes; from the human forgetting curve, Ds can be set to 30 minutes, 30 × 60 is a conversion of 30 minutes to 1800 seconds, and the fatigue index influences the memory strength base value Mfa to show how much the fatigue degree influences the memory strength value at most, and the longer the learning time, the more tired the user and the less the memory strength value is increased and decreased, and conversely, the greater the memory strength value is increased and decreased. The fatigue influence value is obtained by considering the influence on the memory ability from the physiological rule of the human body, the increase and decrease of the memory intensity value are calculated more accurately and finely, the fatigue influence value Mfa is obtained according to a human forgetting curve, and the value is 4 in the embodiment.

The increased or decreased memory intensity value further comprises a difficulty impact value, and the difficulty impact value is calculated by the following formula: df ═ Dti × Mdt, (Dm + Am), Dm ═ Rwr × λ, Rwr ═ Crw/Crt; df is a difficulty influence value, Dti is a difficulty index, Mdt is a difficulty index influence memory strength basic value, Dm is learning data calculation difficulty, Am is manual labeling difficulty, Rwr is the error rate of responding to the new words in the user review process, lambda is a difficulty mark, Crw is the sum of times of responding to the new words in the user review process and the initial learning process, and Crt is the total times of responding to the new words in the user review process.

By adopting the scheme, the difficulty influence value can comprise the manual labeling difficulty and the learning data calculation difficulty, for example, the manual labeling difficulty is the difficulty of a word or a sentence, and is reflected in the aspects of length, word forming rule, Chinese explanation and the like, the words with more letters than less letters are difficult to remember, the difficult to remember with regular letter arrangement is more difficult than the difficult to remember without rule, and the different difficulties of different words are required to be manually labeled for distinguishing; the learning data calculation difficulty is calculated through the error rate of the user answering the words; the difficulty mark lambda is used for calculating the learning data calculation difficulty and can be displayed on a response interface in the form of an energy grid, the difficulty index influences the memory intensity basic value Mdt to be determined according to the overall assignment condition and a human forgetting curve and is expressed as the influence of word difficulty on the memory intensity value, and the Mdt value of the embodiment is 3; λ can be 5 and is represented as 5 difficulty grids in fig. 3, meaning how much the error rate can most affect Dm.

By adopting the scheme, G1 is a gear influence added value, the wrong answer engine constant Reg is determined according to a human forgetting curve, and the value can be 6 in the embodiment.

By adopting the scheme, G2 is a gear influence reduction value, and the answer engine constant Weg is determined according to a human forgetting curve, and the value can be 7.5 in the embodiment.

It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present invention without departing from the principle of the present invention, and those improvements and modifications also fall within the protection scope of the claims of the present invention.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.

It should be understood that the technical problems can be solved by combining and combining the features of the embodiments from the claims.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein, the foregoing description of the disclosed embodiments being directed to enabling one skilled in the art to make and use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating a user's memory level in language translation learning, comprising the steps of:

Acquiring learning information of a user, wherein the learning information comprises the correct rate of answering a learning word by the user;

and generating a gear for evaluating the memory level of the user according to the correct rate of the user to answer the learning words.

2. The method for assessing the memory level of a user in language translation learning according to claim 1, wherein:

the learning information comprises beginner information and review information;

the correct rate of the user to answer the learning word comprises a first correct rate, the first correct rate is represented by a formula of Rrr being Crr/Crt, wherein Rrr is the first correct rate of the user to answer the learning word, Crr is the number of times that the user answers the learning word during the review process, and Crt is the total number of times that the user answers the learning word during the review process.

3. The method for evaluating the memory level of a user in the language translation learning according to claim 1 or 2, wherein:

the learning information further comprises test information;

the correctness of the user answering the learning word comprises a second correctness, and the calculation formula of the second correctness is as follows: rrt ═ i (Crr + Cqr)/(Crt + Cqt), where Rrt is the second rate of correctness, Cqr is the number of times the user answered the learned word in the test, and Cqt is the total number of times the user answered the learned word in the test.

4. The method of claim 3, wherein the number of times the user answers the learning word pair in the test is calculated as:

calculating the optimal review time point after the user finishes learning the words each time according to the learning information to obtain the (N-1) th optimal review time point after the (N-1) th learning is finished, wherein N is the number of times that the user finishes learning the words at the current time;

determining a current testing time point according to the testing information, and calculating a first time interval of Tit-Tq-Tbr 1, wherein Tq is the current testing time point, and Tbr1 is an (N-1) th best review time point;

when Tit < Tx, the increase in Cqr is 0; when Tit > Ts, the incremental value of Cqr is 2; when Tx ≦ Tit ≦ Ts, the incremental value of Cqr is (1+ Tit/Ts); tx is the lower limit interval duration and Ts is the upper limit interval duration.

5. The method of claim 4, wherein the total number of times the user answers the learner word in the test is calculated as:

cqt ═ Cqr + Cqw, the Cqw is the total number of times the user wrote the learned word, the calculation of Cqw is: when Tit < Tx, the increase in Cqw is 2; when Tit > Ts, the incremental value of Cqw is 0; when Tx ≦ Tit ≦ Ts, the incremental value of Cqw is (1-Tit/Ts).

6. The method for evaluating the memory level of a user in the language interpretive learning according to claim 5, wherein the rank of the learning word is calculated as:

receiving the second accuracy;

judging the range of the second accuracy;

and determining the gear according to the range of the second accuracy.

7. The method of claim 6, wherein calculating the (N-1) th best review time point comprises:

8. The method for assessing the memory level of a user in language translation learning according to claim 7, wherein:

9. The method for assessing the memory level of a user in language translation learning according to claim 7, wherein:

judging the times of continuous answering of the learning words;

if the number of times is equal to three times, judging whether the optimal review time point generated after the third answer is finished and the continuous three-time answer pair time are in the same review period;

if yes, setting the optimal review time point generated after the third answer in the next review period.

10. An apparatus for calculating a memory strength of foreign words in language translation learning, comprising: memory, processor and computer program stored on the memory and executable on the processor, which when executed by the processor implements the method of any of the preceding claims 1 to 9.